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Mazviita and I discuss the growing divide between prediction and understanding as neuroscience models and deep learning networks become bigger and more complex. She describes her non-factive account of understanding, which among other things suggests that the best predictive models may deliver less understanding. We also discuss the brain as a computer metaphor, and whether it’s really possible to ignore all the traditionally “non-computational” parts of the brain like metabolism and other life processes.
Show notes:
- Her website.
- Outside color website (with links to more of her publications)
- Her book Outside Color: Perceptual Science and the Puzzle of Color in Philosophy.
- Papers we discuss or mention: